AI/ML Engineering Intern
Daice Labs
Summary
We are hiring an AI/ML Engineering Intern for a 3-6 month internship (with potential for extension) to contribute to our research and engineering efforts remotely within the United States. You will work directly with senior engineers and researchers on active projects, gaining hands-on experience with production ML systems and hybrid AI architectures.
Job description
About the Role
We are hiring an AI/ML Engineering Intern for a 3-6 month internship (with potential for extension) to contribute to our research and engineering efforts remotely within the United States. You will work directly with senior engineers and researchers on active projects, gaining hands-on experience with production ML systems and hybrid AI architectures.
Responsibilities
- Support the design and implementation of machine learning models under the guidance of senior engineers
- Conduct experiments, analyze results, and document findings
- Assist in building and maintaining data pipelines and preprocessing workflows
- Contribute to codebase improvements, testing, and documentation
- Participate in team meetings, code reviews, and technical discussions
Qualifications
- Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Data Science, AI, Machine Learning, or a related field
- Foundational knowledge of machine learning concepts, statistical modeling, and data structures
- Proficiency in Python and familiarity with ML libraries such as PyTorch or TensorFlow
- Experience with data preprocessing and dataset management
- Strong analytical and problem-solving skills
- Clear written and verbal communication skills
- Ability to work independently in a remote environment while meeting deadlines
- Must be authorized to work in the United States
Preferred
- Prior experience contributing to AI/ML research projects or open-source repositories
- Familiarity with hybrid AI approaches, generative models, or symbolic AI
- Experience with version control (Git) and collaborative development workflows
- Coursework or projects in NLP, computer vision, or reinforcement learning
Requirements
- Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Data Science, AI, Machine Learning, or a related field
- Foundational knowledge of machine learning concepts, statistical modeling, and data structures
- Proficiency in Python and familiarity with ML libraries such as PyTorch or TensorFlow
- Experience with data preprocessing and dataset management
- Strong analytical and problem-solving skills
- Clear written and verbal communication skills
- Ability to work independently in a remote environment while meeting deadlines
- Must be authorized to work in the United States
- Prior experience contributing to AI/ML research projects or open-source repositories
- Familiarity with hybrid AI approaches, generative models, or symbolic AI
- Experience with version control (Git) and collaborative development workflows
- Coursework or projects in NLP, computer vision, or reinforcement learning
Benefits
- Paid Internship
- Remote Work
Company overview
Daice Labs is an innovative applied research venture founded by MIT CSAIL scientists that pioneers hybrid AI architectures and adaptive collaboration systems. Based in Brookline, Massachusetts with operations in Stockholm, Sweden, the company operates as a "cofabric" platform where human teams supervise, co-build, and co-own long-horizon outcomes across multiple domains. The company's core mission focuses on developing composite AI systems that are auditable, governable, and adaptive by design, addressing the brittleness of current AI models that perform well on benchmarks but struggle in real-world applications. Daice Labs combines research and product innovation through its "Adapting Machines Research Lab," which explores bio-inspired computing principles and hybrid AI architectures. The company operates as an automated VC-like incubator layer that sponsors builders and backs key products through integrated "Engineering-in-a-Box" workflows with shared context, sandboxed execution, and co-ownership ledgers. With expertise spanning AI/ML, bioengineering, single-cell genomics, and complex systems, Daice Labs represents a new paradigm in collaborative AI development focused on long-horizon execution and programmable adaptation.